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from brown import brown_collection
from consts import SN, SN_
MIN_NS = 10**-7
def NS(noun):
"""
Noun sexiness function
Returns a real value measure of the maximum similarity
a `noun` not in SN has to each noun in SN_
"""
# return MIN_NS for nouns that occur less than 200 times
return brown_collection.tf_idf(noun, SN_)
def AS(adj):
"""
Adjective sexiness function
Returns a real value measure of how likely an adjective `adj`
is to modify a noun in SN
"""
# implementation should return relative frequency of adj
# in sentences in erotica corpus that contain at least
# one noun in SN
return 0
def VS(verb):
"""
Verb sexiness function
Returns a real value measure of how much more likely a verb
phrase `verb` is to appear in an erotic context than a
nonerotic one
"""
# let S_E be the set of sentences in the erotica corpus
# that contain nouns in SN. let S_B be the set of all
# sentences in the Brown corpus. given sentences s with
# verb v
return 0
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